AgenticSystemCore
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- AlicenseNot gradedqualityAmaintenanceLocal research vault over stdio: search, read and link the markdown notes a Claude Code or Codex deep-research pipeline collected, list and check sources, and fetch new URLs into the vault.340 PyPI3,864MIT
- AlicenseNot gradedqualityCmaintenanceEnables reading, writing, and searching a local markdown-based memory store using MCP tools, with safety checks and index consistency.MIT
- AlicenseNot gradedqualityBmaintenanceExposes a living systems memory vault to autonomous agents, letting them search notes with BM25 ranking, read sections within token budgets, extract API/port/schema contracts, compute dependency blast radius, and run machine-verifiable invariant assertions before mutating code. It also supports surgical frontmatter edits, schema linting, wikilink integrity checks, and worklog recording, over stdio MCP.MIT
- AlicenseBqualityDmaintenanceLocal Markdown-backed memory tools for Codex and other MCP-capable agents. Exposes durable agent knowledge via CLI and MCP server.5MIT
- FlicenseNot gradedqualityAmaintenanceEnables MCP-capable coding agents to query a self-hosted, LLM-compiled Markdown knowledge base through a single ask tool that answers from whole wiki articles and returns citations back to the source pages. Supports both local stdio and remote streamable-HTTP transports, with no embeddings or vector store involved.-
- AlicenseNot gradedqualityAmaintenanceEnables agents to read, navigate, and query long-term memory stored as readable, reviewable source files, exposing paged catalogs, indexed searches that explain their misses, bounded relation traces, link diagnostics, raw file access, and preflight checks of drafts against MUST constraints. It serves this read-only by default over stdio so any MCP client can start from a memory catalog and keep reading toward the answer instead of relying on a single similarity guess.1MIT
TDQS
Scored across 7 tools
Two pairs overlap meaningfully: ask vs search both retrieve items (differing mainly in whether a model/description output is used), and propose vs remember both return Proposal payloads (one retrieves an existing payload, one synthesizes a draft). read/links/compose are clearly distinct, and descriptions do clarify the boundaries, but an agent could still misselect within the retrieval and proposal pairs.
Nearly all tools are single lowercase verbs (ask, compose, propose, read, remember, search), giving a predictable style. The lone outlier is 'links', a noun that names a resource rather than an action, a minor deviation from an otherwise consistent convention.
Seven tools is a well-scoped set for a memory/knowledge core, covering retrieval, traversal, composition, and proposal drafting without redundancy. Each tool has a plausible distinct role in the workflow.
Query and draft coverage is good (read, search, ask, links, compose, remember, propose), but the surface stops at proposals: both propose and remember explicitly perform no write, and there is no apply/commit tool or any update/delete of existing items. Agents can draft but cannot persist changes, a notable lifecycle gap.